{"id":"https://openalex.org/W3096263701","doi":"https://doi.org/10.1109/isbi48211.2021.9434131","title":"Post Training Uncertainty Calibration Of Deep Networks For Medical Image Segmentation","display_name":"Post Training Uncertainty Calibration Of Deep Networks For Medical Image Segmentation","publication_year":2021,"publication_date":"2021-04-13","ids":{"openalex":"https://openalex.org/W3096263701","doi":"https://doi.org/10.1109/isbi48211.2021.9434131","mag":"3096263701"},"language":"en","primary_location":{"id":"doi:10.1109/isbi48211.2021.9434131","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi48211.2021.9434131","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://lirias.kuleuven.be/handle/123456789/667366","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5074683809","display_name":"Axel-Jan Rousseau","orcid":"https://orcid.org/0000-0002-5662-1135"},"institutions":[{"id":"https://openalex.org/I878454856","display_name":"Hasselt University","ror":"https://ror.org/04nbhqj75","country_code":"BE","type":"education","lineage":["https://openalex.org/I878454856"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Axel-Jan Rousseau","raw_affiliation_strings":["I\u2010BioStat, Data Science Institute, Hasselt University Belgium"],"affiliations":[{"raw_affiliation_string":"I\u2010BioStat, Data Science Institute, Hasselt University Belgium","institution_ids":["https://openalex.org/I878454856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027119845","display_name":"Thijs Becker","orcid":"https://orcid.org/0000-0003-3432-783X"},"institutions":[{"id":"https://openalex.org/I878454856","display_name":"Hasselt University","ror":"https://ror.org/04nbhqj75","country_code":"BE","type":"education","lineage":["https://openalex.org/I878454856"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Thijs Becker","raw_affiliation_strings":["I\u2010BioStat, Data Science Institute, Hasselt University Belgium"],"affiliations":[{"raw_affiliation_string":"I\u2010BioStat, Data Science Institute, Hasselt University Belgium","institution_ids":["https://openalex.org/I878454856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5035292977","display_name":"Jeroen Bertels","orcid":"https://orcid.org/0000-0001-7206-2671"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Jeroen Bertels","raw_affiliation_strings":["Processing Speech and Images,Department of Electrical Engineering,KU Leuven,Belgium"],"affiliations":[{"raw_affiliation_string":"Processing Speech and Images,Department of Electrical Engineering,KU Leuven,Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077783791","display_name":"Matthew B. Blaschko","orcid":"https://orcid.org/0000-0002-2640-181X"},"institutions":[{"id":"https://openalex.org/I99464096","display_name":"KU Leuven","ror":"https://ror.org/05f950310","country_code":"BE","type":"education","lineage":["https://openalex.org/I99464096"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Matthew B. Blaschko","raw_affiliation_strings":["Processing Speech and Images,Department of Electrical Engineering,KU Leuven,Belgium"],"affiliations":[{"raw_affiliation_string":"Processing Speech and Images,Department of Electrical Engineering,KU Leuven,Belgium","institution_ids":["https://openalex.org/I99464096"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053819400","display_name":"Dirk Valkenborg","orcid":"https://orcid.org/0000-0002-1877-3496"},"institutions":[{"id":"https://openalex.org/I878454856","display_name":"Hasselt University","ror":"https://ror.org/04nbhqj75","country_code":"BE","type":"education","lineage":["https://openalex.org/I878454856"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Dirk Valkenborg","raw_affiliation_strings":["I\u2010BioStat, Data Science Institute, Hasselt University Belgium"],"affiliations":[{"raw_affiliation_string":"I\u2010BioStat, Data Science Institute, Hasselt University Belgium","institution_ids":["https://openalex.org/I878454856"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5074683809"],"corresponding_institution_ids":["https://openalex.org/I878454856"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00581904,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1052","last_page":"1056"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11775","display_name":"COVID-19 diagnosis using AI","score":0.9958000183105469,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10522","display_name":"Medical Imaging Techniques and Applications","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.6947234869003296},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6831517815589905},{"id":"https://openalex.org/keywords/dropout","display_name":"Dropout (neural networks)","score":0.6738155484199524},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.6313166618347168},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5514072179794312},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5264657139778137},{"id":"https://openalex.org/keywords/post-hoc","display_name":"Post hoc","score":0.48463279008865356},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.4781675934791565},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47594642639160156},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3715563118457794},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.36694520711898804},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.31640106439590454},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19654971361160278}],"concepts":[{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.6947234869003296},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6831517815589905},{"id":"https://openalex.org/C2776145597","wikidata":"https://www.wikidata.org/wiki/Q25339462","display_name":"Dropout (neural networks)","level":2,"score":0.6738155484199524},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.6313166618347168},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5514072179794312},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5264657139778137},{"id":"https://openalex.org/C2992886853","wikidata":"https://www.wikidata.org/wiki/Q18381816","display_name":"Post hoc","level":2,"score":0.48463279008865356},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.4781675934791565},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47594642639160156},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3715563118457794},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.36694520711898804},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31640106439590454},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19654971361160278},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C199343813","wikidata":"https://www.wikidata.org/wiki/Q12128","display_name":"Dentistry","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/isbi48211.2021.9434131","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isbi48211.2021.9434131","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI)","raw_type":"proceedings-article"},{"id":"pmh:oai:lirias2repo.kuleuven.be:123456789/667366","is_oa":true,"landing_page_url":"https://lirias.kuleuven.be/handle/123456789/667366","pdf_url":null,"source":{"id":"https://openalex.org/S4306401954","display_name":"Lirias (KU Leuven)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I99464096","host_organization_name":"KU Leuven","host_organization_lineage":["https://openalex.org/I99464096"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"IEEE international symposium on biomedical imaging - ISBI 2021, ONLINE DUE TO COVID-19, 13-16 April 2021","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:arXiv.org:2010.14290","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2010.14290","pdf_url":"https://arxiv.org/pdf/2010.14290","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:documentserver.uhasselt.be:1942/34686","is_oa":false,"landing_page_url":"http://hdl.handle.net/1942/34686","pdf_url":null,"source":{"id":"https://openalex.org/S4306401926","display_name":"Document Server@UHasselt (UHasselt)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I878454856","host_organization_name":"Hasselt University","host_organization_lineage":["https://openalex.org/I878454856"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"},{"id":"doi:10.48550/arxiv.2010.14290","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2010.14290","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"mag:3096263701","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:lirias2repo.kuleuven.be:123456789/667366","is_oa":true,"landing_page_url":"https://lirias.kuleuven.be/handle/123456789/667366","pdf_url":null,"source":{"id":"https://openalex.org/S4306401954","display_name":"Lirias (KU Leuven)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I99464096","host_organization_name":"KU Leuven","host_organization_lineage":["https://openalex.org/I99464096"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"IEEE international symposium on biomedical imaging - ISBI 2021, ONLINE DUE TO COVID-19, 13-16 April 2021","raw_type":"info:eu-repo/semantics/publishedVersion"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1567512734","https://openalex.org/W1618905105","https://openalex.org/W1641498739","https://openalex.org/W1901129140","https://openalex.org/W2103328396","https://openalex.org/W2254249950","https://openalex.org/W2484736472","https://openalex.org/W2600383743","https://openalex.org/W2751069891","https://openalex.org/W2810337461","https://openalex.org/W2892924241","https://openalex.org/W2900298334","https://openalex.org/W2959828872","https://openalex.org/W2963238274","https://openalex.org/W2964059111","https://openalex.org/W2964144363","https://openalex.org/W2964212410","https://openalex.org/W3015910149","https://openalex.org/W3035546112","https://openalex.org/W3092059180","https://openalex.org/W3098712157","https://openalex.org/W6617145748","https://openalex.org/W6636501900","https://openalex.org/W6639824700","https://openalex.org/W6691692454","https://openalex.org/W6730042731","https://openalex.org/W6735443497","https://openalex.org/W6739651123","https://openalex.org/W6753033005","https://openalex.org/W6755891590"],"related_works":["https://openalex.org/W3130729685","https://openalex.org/W3111643701","https://openalex.org/W3199220067","https://openalex.org/W3133962266","https://openalex.org/W2974098375","https://openalex.org/W108026892","https://openalex.org/W2625850613","https://openalex.org/W2474729660","https://openalex.org/W2196231785","https://openalex.org/W3208788144","https://openalex.org/W2011171269","https://openalex.org/W2549316618","https://openalex.org/W2598379669","https://openalex.org/W3041660580","https://openalex.org/W257165822","https://openalex.org/W1736326563","https://openalex.org/W3182387658","https://openalex.org/W263118555","https://openalex.org/W3100970744","https://openalex.org/W2791542528"],"abstract_inverted_index":{"Neural":[0],"networks":[1,66],"for":[2],"automated":[3],"image":[4],"segmentation":[5],"are":[6,44,51,54,62,88],"typically":[7],"trained":[8,67,84,95],"to":[9,19,46,56,64,143],"achieve":[10],"maximum":[11],"accuracy,":[12],"while":[13],"less":[14,91],"attention":[15],"has":[16],"been":[17],"given":[18],"the":[20,34,109,116,144,150],"calibration":[21,41,132,140,151],"of":[22,49,149],"their":[23],"confidence":[24,28],"scores.":[25],"However,":[26],"well-calibrated":[27],"scores":[29],"provide":[30],"valuable":[31],"information":[32],"towards":[33],"user.":[35],"We":[36],"investigate":[37],"several":[38],"post":[39,105,130],"hoc":[40,106,131],"methods":[42],"that":[43],"straightforward":[45],"implement,":[47],"some":[48],"which":[50],"novel.":[52],"They":[53,61],"compared":[55,142],"Monte":[57],"Carlo":[58],"(MC)":[59],"dropout.":[60,137],"applied":[63],"neural":[65],"with":[68,135],"cross-entropy":[69],"(CE)":[70],"and":[71,79],"soft":[72],"Dice":[73],"(SD)":[74],"losses":[75],"on":[76,85,96,122],"BraTS":[77],"2018":[78],"ISLES":[80],"2018.":[81],"Surprisingly,":[82],"models":[83],"SD":[86],"loss":[87],"not":[89],"necessarily":[90],"calibrated":[92],"than":[93],"those":[94],"CE":[97],"loss.":[98],"In":[99,127],"all":[100,128],"cases,":[101,129],"at":[102],"least":[103],"one":[104,123],"method":[107,124],"improves":[108,141],"calibration.":[110],"There":[111],"is":[112,133],"limited":[113],"consistency":[114],"across":[115],"results,":[117],"so":[118],"we":[119],"can't":[120],"conclude":[121],"being":[125],"superior.":[126],"competitive":[134],"MC":[136],"Although":[138],"average":[139],"base":[145],"model,":[146],"subject-level":[147],"variance":[148],"remains":[152],"similar.":[153]},"counts_by_year":[],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
